• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.935-943
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• 2013

Man-heo-Jeong, which was located in the middle of the Sibri bamboo grove near by Tae-hwa river in Ulsan, was a Jeong-ja(a kind of pavilion) by Park Chui-moon, both a military officer and a nationwide town chief. Now we can presume the appearance of Man-heo-Jeong, referring to the old map describing old Ulsan districts and to old literatures of Park Chui-moon's family describing downtown of Ulsan of that times. It is estimated that the size of Manheo-Jung was constructed three-bay in front view, one point half-bay in side view and terrace in the fore front. Its space composition was designed likewise one-bay was both sides and in the middle there was one-bay Maru called joong-dang-hyeob-sil type. Such a structure made people to enter from the back entrance of gazabo and look the front view dramatically.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.457-466
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• 2010

In this paper, we propose a new method for detecting digital forgery that identify interpolated region between digital composited images. For detecting the interpolation factor and the tampered regions, we perform two algorithms: The first algorithm is to estimate the interpolation factors using the differential equation for forgery image along the horizontal, vertical, and diagonal directions, respectively; The second algorithm is to scan the interpolation factors along each direction for detection areas as the mask of the optical window size($64{\times}64$) in order to find out the forgery region. A detection map of the forgery is classified with the magnitude of estimated interpolation factors into colors. This detection map can be used to find out interpolated regions from the tampered image. Experimental results demonstrate the proposed algorithms are proven on several examples. We also show the proposed approach is to accurately detect interpolated regions from digital composite images.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.48-57
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• 2020

Recently, with the rapid development of image recognition technology, the demand for object analysis in road CCTV videos is increasing. In this paper, we propose a method that can adaptively find the counting line for traffic analysis in road CCTV videos. First, vehicles on the road are detected, and the corresponding positions of the detected vehicles are modeled as the two-dimensional pointwise Gaussian map. The paths of vehicles are estimated by accumulating pointwise Gaussian maps on successive video frames. Then, we apply clustering and linear regression to the accumulated Gaussian map to find the principal direction of the road, which is highly relevant to the counting line. Experimental results show that the proposed method for detecting the counting line is effective in various situations.

• Journal of the Korean Society of Propulsion Engineers
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• v.12 no.1
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• pp.51-56
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• 2008

In this work the realistic install performance analysis of a helicopter was performed together with power extraction enabling to operate auxiliary system as well as intake pressure loss, loss due to bleed air, etc. which must be considered in practical propulsion system's performance modelling to be installed to the airframe. The pressure loss occurring in intake was estimated from the intake performance map with relationships of Mach Number and pressure loss. In order to evaluate the proposed installed performance model, the experimental data for comparison must be needed when mounted in propulsion system. However because of lack of accessibility to such real data at the moment, the alternative way was made through comparison that the analysis results by the proposed model were compared with a wellknown commercial program GASTURB's analysis results. The validity of the proposed installed performance model was consequently confirmed because its average deferences from the GASTURB's results were within 0.5%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.921-926
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• 2006

The Presence of a line-of-sight(LoS) blockage can degrade the UWB positioning accuracy for two reasons. Firstly, it makes estimation of the time of arrival(ToA) of the direct path signal difficult by complicating the multipath structure of the propagation channel. Secondly, the higher dielectric constant of the LoS blocking material than that of free space introduces excess propagation delay which will bias the range estimation. In this paper, methods based on ray tracing to reduce the ranging error resulting from the second reason are Posed. We take two different approaches; a statistical approach and a map-aided method. In the statistical approach, we establish a conditional distribution of the excess propagation delay caused by LoS blockages using a ray tracing technique. The lo6wer bound of the ranging performance based on this model is estimated. Ine ray tracing method is also used for the map-aided ToA positioning approach. UWB propagation measurement data taken in an office environment is used to examine the performance of this method.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.329-338
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• 2011

The time-series normalized difference vegetation index (NDVI) product has proven to be a powerful tool to investigate the phenological information because it can monitor the change of the forests with very high time-resolution, This study described the application of the DFT analysis over the 9 year MODIS data for the identification of the two types of vegetation cover, Pinus densiflora(Pd) and Querqus mongolica(Qm) which are dominant species of evergreen and broadleaved deciduous forest, respectively, The total number of samples was 5148 reference cycles which consist of 2160 Pd and 2988 Qm. They were extracted from the pixel-based MODIS scenes over the 9 years from 2000 to 2008 of South Korea. The DFT analysis was mainly focused on the 0th and $1^{st}$ harmonic components, each of which represents the mean value and the variation amplitude of the NDVI over the years, respectively. The $0^{th}$ harmonic values of the vegetation Pd and Qm averaged over the 9 years were 0.74 and 0.65, respectively. This implies that Pd has a higher NDVI than Qm. Similarly obtained $1^{st}$ harmonic values of Pd and Qm were 0.19 and 0.27, respectively. This can be intuitively understood considering that the seasonal variation of Qm is much larger than Pd. This distinctive difference of the $1^{st}$ harmonic value has been used to identify evergreen and deciduous forests. Overall agreement between the Fourier analysis-based map and the actal vegetation map has been estimated to be as high as 75%. This study found that the DFT analysis can be a concise and repeatable method to separate and trace the changes of evergreen and deciduous forest using the annual NDVI cycles.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.661-670
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• 2018

This study aims to develop a methodology of convolutional neural networks (CNNs) to produce thematic maps from remote sensing data. Optimizing the image size for CNNs was studied, since the size of the image affects to accuracy, working as hyper-parameter. The selected study area is Mt. Ung, located in Dangjin-si, Chungcheongnam-do, South Korea, consisting of both coniferous forest and deciduous forest. Spatial structure analysis and the classification of forest type using CNNs was carried in the study area at a diverse range of scales. As a result of the spatial structure analysis, it was found that the local variance (LV) was high, in the range of 7.65 m to 18.87 m, meaning that the size of objects in the image is likely to be with in this range. As a result of the classification, the image measuring 15.81 m, belonging to the range with highest LV values, had the highest classification accuracy of 85.09%. Also, there was a positive correlation between LV and the accuracy in the range under 15.81 m, which was judged to be the optimal image size. Therefore, the trial and error selection of the optimum image size could be minimized by choosing the result of the spatial structure analysis as the starting point. This study estimated the optimal image size for CNNs using spatial structure analysis and found that this can be used to promote the application of deep-learning in remote sensing.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.1-10
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• 2003

RUSLE(revised universal soil loss equation) has been widely used for estimating soil loss. It is very difficult to validate the model estimation since the calculated soil loss should be compared with the survey data for quantification. The input variables for RUSLE model were estimated to grid cell for raster analysis in Bosung basin. Both reconnaissance(1:250,000) and detailed(1:25,000) soil maps were used to derive the input variables for soil erodibility factor. Soil loss calculated using RUSLE were compared to the unit sediment deposit surveyed by KICT(Korea Institute of Construction Technology, 1992) in Bosung basin for assessment. Unit sediment deposit from the cell size of 120m and 150m were the closest to the survey data in 1:250,000 and 1:25,000 map scale, respectively.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.243-248
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• 2013

In this paper, depth of foreground is analysed by focus and color analysis grouping for 2D/3D video conversion and depth of foreground progressing method is preposed by using focus and motion information. Candidate foreground image is generated by estimated movement of image focus information for extracting foreground from 2D video. Area of foreground is extracted by filling progress using color analysis on hole area of inner object existing candidate foreground image. Depth information is generated by analysing value of focus existing on actual frame for allocating depth at generated foreground area. Depth information is allocated by weighting motion information. Results of previous proposed algorithm is compared with proposed method from this paper for evaluating the quality of generated depth information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.277-284
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• 2004

The subject of this study is to apply experimentally In resolution stereo imagery of IKONOS to producing 1:50,000 scale maps for Munsan area in Paju, being near the Military Demarcation Line, is inaccessible for aerial photography. Ground control points were acquired from GPS surveying to perform geometric corrections on images. Digital maps were produced from IKONOS stereo imagery on the digital photographic workstation. From field investigation, RMS errors of the plane and vertical positions are estimated respectively at $\pm$1.706m and $\pm$1.231m, respectively. These plane and vertical accuracies are within the tolerance limits of those provided in the NGIS Digital Topographic Map Production Rules. Therefore this suggested method is recommended for producing the large scale digital maps of 'No flight' zone near the M.D.L.